Agriculture and Natural Resources, Institute of (IANR)
Forensic Science: Faculty and Staff Publications
Date of this Version
2022
Document Type
Article
Citation
MDPI Genes (2022) 13: 1429
doi: 10.3390/genes13081429
Academic editors: Chiara Turchi and Piero Fariselli
Abstract
Mixed human deoxyribonucleic acid (DNA) samples present one of the most challenging pieces of evidence that a forensic analyst can encounter. When multiple contributors, stochastic amplification, and allele drop-out further complicate the mixture profile, interpretation by hand becomes unreliable and statistical analysis problematic. Probabilistic genotyping software has provided a tool to address complex mixture interpretation and provide likelihood ratios for defined sets of propositions. The MaSTR™ software is a fully continuous probabilistic system that considers a wide range of STR profile data to provide likelihood ratios on DNA mixtures. Mixtures with two to five contributors and a range of component ratios and allele peak heights were created to test the validity of MaSTR™ with data similar to real casework. Over 280 different mixed DNA profiles were used to perform more than 2600 analyses using different sets of propositions and numbers of contributors. The results of the analyses demonstrated that MaSTR™ provided accurate and precise statistical data on DNA mixtures with up to five contributors, including minor contributors with stochastic amplification effects. Tests for both Type I and Type II errors were performed. The findings in this study support that MaSTR™ is a robust tool that meets the current standards for probabilistic genotyping.
Included in
Criminology and Criminal Justice Commons, Forensic Science and Technology Commons, Social Control, Law, Crime, and Deviance Commons
Comments
Copyright 2022, the authors. Open access
License: CC BY 4.0